Module 5: Amazon Bedrock Application Components Applications and use cases Overview of generative AI application components Foundation models and the FM interface Working with datasets and embeddings Demonstration: Word Embeddings Additional application components RAG Model fine-tuning Securing generative AI applications Generative AI application architecture

Module 6: Amazon Bedrock Foundation Models Introduction to Amazon Bedrock foundation models Using Amazon Bedrock FMs for inference Amazon Bedrock methods Data protection and auditability Demonstration: Invoke Bedrock Model for Text Generation Using Zero-Shot Prompt

Module 7: LangChain Optimizing LLM performance Integrating AWS and LangChain Using models with LangChain Constructing prompts Structuring documents with indexes Storing and retrieving data with memory Using chains to sequence components Managing external resources with LangChain agents Demonstration: Bedrock with LangChain Using a Prompt that Includes Context

Module 8: Architecture Patterns Introduction to architecture patterns Text summarization Demonstration: Text Summarization of Small Files with Anthropic Claude Demonstration: Abstractive Text Summarization with Amazon Titan Using LangChain Question answering Demonstration: Using Amazon Bedrock for Question Answering Chatbots Demonstration: Conversational Interface – Chatbot with AI21 LLM Code generation Demonstration: Using Amazon Bedrock Models for Code Generation LangChain and agents for Amazon Bedrock Demonstration: Integrating Amazon Bedrock Models with LangChain Agents